Crisis Narratives and Topics of the COVID-19 Pandemic on Finnish Twitter

Abstract

Narratives are central to the human experience because they inform how we make sense of the complex world around us. When the COVID-19 pandemic forced people to stay home and avoid physical contact, narratives of the evolving crisis were actively told on Twitter. In this thesis, I analyse crisis narratives and their development on Finnish Twitter. I use a dataset of 375,322 tweets that were collected between January 2020 and August 2021. The data are analysed with the help of topic modelling, a machine-learning method that is used to discover latent topics from large collections of texts. The most common topics and their temporal distribution as well as tweets that are strongly associated with these topics are analysed within the theoretical framework of crisis and narrative studies. The results show that the most common topics were related to the measures put in place to control the spread of the virus. The COVID-19 pandemic appeared to many as a crisis of regulations rather than as a health crisis. As relatively few people were affected by the virus itself, the crisis narratives shared on Twitter were more concerned with the impact the everchanging restrictions and guidelines had on people’s everyday lives than the foreign threat imposed by the virus. These results provide insight into the ways in which crises are constructed in narrative and thus can be used to better understand how future crises emerge and evolve.